generic programming using adaptive and aspect-oriented programming

04/22/23 Generic Programming/Dagstuhl 1

Generic Programming using Adaptive and Aspect-Oriented

ProgrammingKarl Lieberherr, The Demeter Group

College of Computer ScienceNortheastern University, Boston


Overview

• Generic programming• Aspect-oriented and Adaptive Programming• Adaptive Plug-and-Play Components

– Pricing Policies (from an IBM code generator)– Graph Algorithms (Cycle checking)

• Demeter/Java• Conclusions


What is Generic Programming?

• Expressing algorithms with minimal assumptions about data abstractions, and vice versa, thus making them as interoperable as possible

• Lifting of a concrete algorithm to as a general level as possible without losing efficiency



• Lifting of a concrete algorithm to as a general level as possible without losing efficiency i.e., the most abstract form such that when specialized back to the concrete case the result is just as efficient as the original algorithm.

• From Dagstuhl 98 conference on generic programming



• Generic programming is about making programs more adaptable by making them more general

• Embody non-traditional kinds of polymorphism

• Parameters of a generic program are rich in structure (programs, types, graphs).

• From Workshop on Gen. Prog. Sweden 98


How does Aspect-Oriented Programming help?

• Tease out bigger chunks than classes• Tease out issues which cross-cut many classes• Describe different issues separately making

minimal assumptions among them: Avoid tangling of issues

• Express issues by aspect descriptions which are compiled into behavior by a weaver


Many evolution problems come from tangled designs/programs

• Code for a requirement is spread through many artifacts. In each artifact, code for different requirements is tangled together.

• For example:– Information structure is tangled with behavior.

We want structure-shyness (Lieberherr ‘92). – Synchronization code is tangled with sequential

code.


Eliminating drawbacks with Aspect-Oriented Programming

(AOP)

• Solution: Split software into cooperating, loosely coupled components and aspect-descriptions.

• Untangles designs/programs and eliminates redundancy.

• Aspect description examples: marshalling, synchronization, information structure etc.


Cross-cutting of components and aspectsordinary program

structure-shyfunctionality

structure

synchronization

better programeasier to understand!

Components

Aspect 1

Aspect 2


What is adaptive programming (AP)? A special case of AOP

• One of the aspects or the components use graphs which are referred to by traversal strategies.

• A traversal strategy defines traversals of graphs without referring to the details.

• Adaptive programming is aspect-oriented programming with traversal strategies.


Flexibility versus Complexity

• AP adds flexibility• BUT simplifies designs and programs• Partial evaluation makes efficient

04/22/23 Generic Programming/Dagstuhl 12warm climate cold climate

same seeds in different climates: similar treessame strategy in different class graphs: similar traversals

Families: Nature Analogy for AP


Why Traversal Strategies?• Law of Demeter: a method should talk only to its friends: arguments and part objects (computed or stored) and newly created objects

• Dilemma:•If followed: Small method problem of OO•If not followed: Unmaintainable code

•Traversal strategies are the solution to this dilemma

Widely used, for example, at JPLfor the Mars exploration software.

10 yearanniversary

Graph patterns: for implementing patterns


Software Architecture View

• Software architectures where connections necessary for a specific behavior are specified approximately, yet precisely, using regular expression-like constructs.

• Improves on conventional architectures by supporting structure-shyness allowing both simpler and more flexible architectures.


Implementation of traversal strategies

• Based on novel applications and variations of standard techniques:– Intersection of non-deterministic finite

automata– Simulation of non-deterministic finite automata


How to do the interesting work?

• Traversal strategies only navigate.• Visitors and adaptive plug and play

components (APPCs) specify what is done in addition to navigation.

• APPCs– change group of classes during a traversal – plug-and-play organization based on ports– parameterized by traversal strategies


Adaptive Plug-and-Play Components (APCCs)

• Specify two interfaces – to the class structure they are

supposed to visit– to other APPCs they may be

connected to


APPC Pricing

Interface

s1 = from lineItem: LineItemParty via item: ItemParty to charges: ChargesParty; s2 = from lineItem: LineItemParty to pricer: PricerParty; s3 = from lineItem: LineItemParty to customer: Customer;

PricerParty [Float basicPrice(ItemParty item); Integer discount(ItemParty item, Integer qty, Customer: customer); ]

ChargesParty [Float cost(Integer qty, Float unitP, ItemParty: item ); ]


APPC Pricing Behavior LineItemParty {

public Float price (Integer qty ){Float basicPrice, unitPrice; Integer discount; basicPrice = pricer.basicPrice();discount = pricer.discount(item, qty, customer); unitPrice = basicPrice - (discount * basicPrice); return (unitprice + additionalCharges(unitPrice, qty)); }

Float additionalCharges(float unitP, Integer qty) {

Interger total = 0; during s1 {

ChargesParty{total += cost(qty, unitP, item); } return total;} }

} }


Let us generate different pricing schemes out of the generic pricing component specified by the pricing adaptive plug-and-play component …

• Scheme 1: Regular Pricing

each product has a base price which can be discounted depending on the number of the units ordered

• Scheme 2: Negotiated Pricing:

A customer may have negotiated certain prices and discounts for particular items


Scheme 1: Regular Price

Quote::+ {float regPrice() = Pricing with { LineItemParty = Quote; PriceParty = HWProduct

[basicPrice = regPrice; discount = regDiscount;]

ItemParty = HWProduct; ChargesParty = Tax

[cost = taxCharge] }} Roles

LineItemParty PricePartyItemPartyChargesParty

Played byQuoteHWProductTax


Scheme 2: Negotiated Price

Quote::+ {Float negPrice() = Pricing with { LineItemParty = Quote; PriceParty = Customer;

[basicPrice = negProdPrice; discount = negProdDiscount;]

ItemParty = HWProduct; ChargesParty = Tax;

[cost = taxCharge] }} Roles

LineItemParty PricePartyItemPartyChargesParty

Played byQuoteCustomerHWProductTax


Graph algorithmsMarking: Basic Marking AlgorithmCycle: Cycle Checking additionConnected: Connected Component Addition


APPC Marking {

Interface s = from Graph to Adjacency to Vertex to Adjacency Behavior Adjacency {

bool marked = false;myRole() { bool visited = marked; if (marked == false) { marked = true; next()}; return visited;}

} }


APPC Connectivity {

Interface s: from Graph to-stop Adjacency

Behavior Integer count = 0;return count;Adjacency {

myRole() { if ( next() == false ) { count += 1; } }

} }


APPC CycleCheck {

Interface s = from Graph to Adjacency to Vertex to Adjacency

BehaviorStack stack = Stack new();Adjacency {

myRole() { if (stack.includes(this)) {

System.out.printIn(``cycle'' + stack.print) }else { stack.add(this); } next(); stack.remove(this);

}}

}


Want to do connectivity and cycle check simultaneously


ConnectivityAndCycleCheck = (Connectivity compose DGCycleCheck) (Marking)

(Connectivity => CycleCheck => Marking, {Connectivity, CycleCheck} <= Marking)

// INSTANTIATING FOR CONCRETE GRAPH STRUCTUREs = Network via Adjacency through neighbors via Node through <-source

to AdjacencyNetwork ::+ {void connectivityAndCycleCheck()

= ConnectivityAndCycleCheck during s} with {Network = Graph; Node = Vertex; }


Adaptive Plug-and-Play Components

• Builds on Batory’s mixin layers (ECOOP 98) and supports adaptiveness by parameterization with traversal strategies

• Modification of a group of collaborating classes

• Encapsulate group of related adaptive programs


Goal of Demeter/Java• Avoid code tangling and redundancy

– traversal strategies and visitors untangle structure and behavior

– visitors and adjusters untangle code for distinct behaviors

– COOL untangles synchronization issues and behavior

– RIDL untangles remote invocation issues and behavior and structure

Tools using Demeter ideas: Demeter/C++, Demeter/CLOS (BBN), Demeter/Perl5 (MIT), AspectJ (Xerox PARC)


Success indicators• Used in several commercial projects (HP

(printer family installation), GTE (compiler), Motorola (pattern generator), Novell (schema comparator)

• AspectJ from Xerox PARC based on Cristina Lopes Ph.D. thesis (1998) at Northeastern University supported by Xerox PARC.


Success indicators: Commercialization effort

StructureBuilder from Tendril Software Inc.

Has support for traversals and generates code controlled by structure.

www.tendril.com


Conclusions

• APPCs as a useful abstraction for generic programming

• How to use them with C++ and STL: simulate them using the visitor design pattern

• Traversal strategies are a key component of APPCs


Some Connections

• Complete traversals: APPCs need that too• Polytypic Programming: APPCs are

polytypic• Konstanz team: Generic graph algorithms:

APPCs seem to help• Traversal Strategy Graphs: can be explained

in terms of temporal logic (CTL formulas)


Partial Evaluation: Ray Tracing

Viewpoint determines howscene appears.

Avoid recomputations fromviewpoint to viewpoint (imagineflying over scene). For example,intersection of objects can be computed once and reused forseveral viewpoints.



Scene(S) ViewPoint(VP)

Scene with light info

P(S,VP)

ViewPoint(VP)

Scene with light info

P(VP)S fixed



Scene(S) ViewPoint(VP)

Output = Scene with light infoin C

P(S,VP)

ViewPoint(VP)

Scene with light infoin C

P(VP)S fixed

In C

PE for CPE for C

PE for C


Partial Evaluation: Adaptive Programming Component

ClassGraph CGObjectGraph OGStrategyGraph SG

OG

Output = Graph Language withcode annotations

P(SG,CG,OG)

OG

Output

P(OG)CG fixedSG fixedAPPCs fixed

SG CG

APPCsPE for graphlanguage PE for graph

language


Similarities

• Ray tracing– freeze scene

– transform program to gain efficiency

– domain specific computation

– use general partial evaluation algorithms

• AP– freeze class graph– freeze strategy graph– transform program to

gain efficiency– general-purpose

computation– use specialized partial

evaluation algorithms (automata intersection)


Similarities

• Ray tracing– use general partial

evaluation algorithms for a programming language such as C.

• AP– use specialized partial

evaluation algorithms (automata intersection)

– partial evaluation is done for a graph language


Partial Evaluation: Adaptive Programming Component

ClassGraph CGObjectGraph OGStrategyGraph SG

OG

Output

P(SG,CG,OG)

OG

Output

P(CG’,OG)CG partially fixedSG fixed

SG CG CG’


Aspect-Oriented Programming



• Background aspects– synchronization– remote invocation

• Foreground aspects– visitors– APPCs



• Implementation requires special purpose partial evaluators. Example:

P(SG,CG,OG)PE for graphlanguage

P(OG)CG fixedSG fixed


Aspect-Oriented Programming• Expansion of aspect description

– bounded• synchronization

– unbounded• structure


STL viewalgorithms data structures

glue = iterators

parameterized byiterators


Demeter viewadaptivealgorithms data structures

glue = traversalstrategies


Demeter view


Demeter View

• Adaptive program: strategies as parameters• Class graph: intended home for traversal

strategies• Glue = traversal strategies = adapt strategy

parameters to specific class graph and check constraints


Traversal strategy types

• Traversal strategy parameters have an interface– a traversal strategy without negative constraints

• express minimal relationships needed– CTL expressions for ordering constraints

(optional)


Modification of objects during traversal

• Validity of a traversal– insertion or deletion

• at point to be traversed• at point already traversed


Plug-and-play

• Has a specific meaning– Self description – Building blocks are enabled to find their own

collaborators– Popular in hardware


APPCs and composition

• Should be able to write programs to compose and configure APPCs?

• Ullrich Koethe: It is sometimes time consuming and error prone to set up collaborations manually. Often, selecting one collaborator implies certain choices of other, related services. If these constraints must be kept manually => reduced reusability


Composition of APPCs

• A => B => C• {A,B} <= C• Not good enough: Need conditionals, loops,

arrays to connect components.

generic programming using adaptive and aspect-oriented programming

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